Chance constrained programming using non-Gaussian joint distribution function in design of standalone hybrid renewable energy systems

Energy

Volumn 66, Issue , 2014, Pages 677-688

  Kamjoo, Azadeh ^a   Maheri, Alireza ^a   Putrus, Ghanim A ^a  

^a NORTHUMBRIA UNIVERSITY   (United Kingdom)

Author keywords

Chance constrained programming; Design under uncertainties; Hybrid wind PV battery; Reliability; Standalone hybrid systems

Indexed keywords

COMPUTER PROGRAMMING; DESIGN; ENERGY POLICY; HYBRID SYSTEMS; MONTE CARLO METHODS; RELIABILITY; TIME SERIES ANALYSIS; COMPUTER SIMULATION; DISTRIBUTION FUNCTIONS; INTELLIGENT SYSTEMS; RENEWABLE ENERGY RESOURCES; SOLAR RADIATION; WIND; WIND TURBINES;

CHANCE-CONSTRAINED PROGRAMMING; DESIGN UNDER UNCERTAINTY; HYBRID RENEWABLE ENERGY SYSTEMS; HYBRID WIND-PV-BATTERY; JOINT DISTRIBUTION FUNCTIONS; MONTE- CARLO SIMULATIONS; STAND-ALONE HYBRID SYSTEM; WIND TURBINE ROTORS; HYBRID WIND; RENEWABLE RESOURCE;

RENEWABLE ENERGY RESOURCES; MONTE CARLO METHODS;

DESIGN METHOD; ELECTRICITY SUPPLY; MONTE CARLO ANALYSIS; RELIABILITY ANALYSIS; RENEWABLE RESOURCE; SIZE; SOLAR RADIATION; STATISTICAL DISTRIBUTION; TIME SERIES ANALYSIS; UNCERTAINTY ANALYSIS; WIND VELOCITY; COMPARATIVE STUDY; GAUSSIAN METHOD; PERFORMANCE ASSESSMENT; SIMULATION; SOLAR POWER; WIND POWER;

EID: 84896403452     PISSN: 03605442     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.energy.2014.01.027     Document Type: Article

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